Abstract
A new application of mate selection is presented in this study that maximizes the expected genetic progress of a selected trait while holding a correlated trait unchanged. The proposed method combines the use of BLUP evaluation and linear programming techniques and its properties have been analyzed by Monte Carlo simulation on a numerical example from beef cattle with selection for weaning weight and restriction on birth weight. With respect to restricted index or BLUP selection, this alternative method allows: (a) a similar response for both the selected and restricted traits, (b) lower variances of the responses and (c) greater robustness against errors in the genetic correlation estimate.
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